Struct renforce::util::approx::VLinear

pub struct VLinear<F: Float + Debug, S: Space> { /* fields omitted */ }

Represents a linear function approximator f(x) = w^T g(x) + b where g: S -> Rⁿ maps states to a vector of features Weights updated using squared error cost C = 1/2(w^T g(x) + b - y)²

Methods

impl<F: Float + Debug, S: Space> VLinear<F, S>

fn new() -> VLinear<F, S>

Creates a new Linear V-Function Approximator

fn with_features(feats: Vec<Box<Feature<S, F>>>) -> VLinear<F, S>

Creates a new Linear V-Function Approximator with the given features

fn add_feature(self, feature: Box<Feature<S, F>>) -> VLinear<F, S>

Adds the specified feature to the end of the feature vector, giving it a random weight

Trait Implementations

impl<F: Debug + Float + Debug, S: Debug + Space> Debug for VLinear<F, S>

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<F: Clone + Float + Debug, S: Clone + Space> Clone for VLinear<F, S>

fn clone(&self) -> VLinear<F, S>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<F: Float + Debug, S: Space> VFunction<S> for VLinear<F, S>

fn eval(&self, state: &S::Element) -> f64

Evaluate the function on the given state

fn update(&mut self, state: &S::Element, new_val: f64, alpha: f64)

Update the function using the given information (alpha is learning rate)

impl<F: Float + Debug, S: Space> ParameterizedFunc<F> for VLinear<F, S>

fn num_params(&self) -> usize

Returns number of parameters used by the function

fn get_params(&self) -> Vec<F>

Returns the parameters used by the function

fn set_params(&mut self, params: Vec<F>)

Changes the parameters used by the function

impl<S: Space, A: Space, F: Float + Debug> FeatureExtractor<S, A, F> for VLinear<F, S>

fn num_features(&self) -> usize

Number of features that can be calculated

fn extract(&self, state: &S::Element, _: &A::Element) -> Vec<F>

Vector containg the values of all the features for this state

impl<S: Space, A: Space, F: Float + Debug> DifferentiableFunc<S, A, F> for VLinear<F, S>

fn get_grad(&self, state: &S::Element, _: &A::Element) -> Vec<F>

Calculates the gradient of the output with respect to this function's parameters

fn calculate(&self, state: &S::Element, _: &A::Element) -> F

Calculates the result of calling function on given input

impl<S: Space> Default for VLinear<f64, S>

fn default() -> VLinear<f64, S>

Creates a new Linear V-Function Approximator